Scott Shen

Intelligent call admission control for wideband CDMA cellular systems

In this paper, we propose intelligent call admission control for wideband code-division multiple-access (CDMA) cellular systems to support differentiated quality-of-service (QoS) requirements, guarantee the forced termination probability of handoffs, and maximize the spectrum utilization. The intelligent call admission controller (ICAC) contains a fuzzy call admission processor to make admission decision for a call request by considering QoS measures such as the forced termination (drop call) probability of handoff, the outage probability of all service types, the predicted next-step existing-call interference, the link gain, and the estimated equivalent interference of the call request. The pipeline recurrent neural network (PRNN) is used to accurately predict the next-step existing-call interference, and the fuzzy logic theory is applied to estimate the new/handoff call interference based on knowledge of effective bandwidth method. Simulation results indicate that ICAC achieves system capacity higher than conventional CAC schemes by an amount of more than 10% in both low and high moving speed cases. Moreover, ICAC can cope with the unpredictable statistical fluctuation of wireless multimedia traffic; it always fulfill QoS requirements for all service types and keep the forced termination probability satisfied, while the CAC of multimedia calls (MCAC) and SIR-based CAC with intercell interference prediction (PSIR-CAC) fail to adapt to the variation of traffic conditions.

A utility-approached radio resource allocation algorithm for downlink in OFDMA cellular systems

In this paper, we propose a utility-approached radio resource allocation (RRA) algorithm for downlink transmission in orthogonal frequency division multiple access (OFDMA) cellular systems. The proposed utility-approached RRA algorithm is to efficiently allocate the radio resource to mobiles according to a utility function, which contains a rate-power function, a QoS function, and a priority function to ensure QoS requirements among heterogenous services and improve the system throughput. Also, a simulated-annealing (SA) method is applied to find out the solution within a reasonable time. Simulation result shows that the proposed utility-approached RRA algorithm can allocate the radio resource efficiently and guarantee the QoS requirements of each user under the power constraints of the OFDMA system.

Neural fuzzy call admission and rate controller for WCDMA cellular systems providing multirate services

The paper proposes a neural fuzzy call admission and rate controller (NFARC) scheme for WCDMA cellular systems providing multirate services. The NFARC scheme can guarantee the quality of service (QoS) requirements and improve the utilization of the system. Simulation results show that the NFARC scheme achieves low forced termination probability and high system capacity even in the bursty traffic conditions. NFARC accepts users more than intelligent call admission controller (ICAC) by an amount of 45.35%.

Intelligent call admission control for differentiated QoS provisioning in wideband CDMA cellular systems

We propose intelligent call admission control for wideband CDMA cellular systems to support differentiated QoS requirements. The intelligent call admission controller (ICAC) adopts fuzzy and neural network techniques to make admission decision for a new call request by considering the QoS measures of all service types, predicted next-step existing-call interference, and estimated new-call interference. It contains a fuzzy call admission processor, a pipeline recurrent neutral network (PRNN) interference predictor and a fuzzy equivalent interference estimator. Simulation results indicate that ICAC attains better performance in keeping QoS guaranteed, blocking probability and admitted number of users. Furthermore, ICAC is more adaptive and stable than SIR-based CAC in wideband CDMA cellular systems.

A cellular neural network and utility-based radio resource scheduler for multimedia CDMA communication systems

The paper proposes a cellular neural network and utility (CNNU)-based radio resource scheduler for multimedia CDMA communication systems supporting differentiated quality-of-service (QoS). Here, we define a relevant utility function for each connection, which is its radio resource function weighted by a QoS requirement deviation function and a fairness compensation function. We also propose cellular neural networks (CNN) to design the utility-based radio resource scheduler according to the Lyapunov method to solve the constrained optimization problem. The CNN is powerful for complicated optimization problems and has been proved that it can rapidly converge to a desired equilibrium; the utility-based scheduling algorithm can efficiently utilize the radio resource for system, keep the QoS requirements of connections guaranteed, and provide the weighted fairness for connections. Therefore, the CNNU-based scheduler, which determines a radio resource assignment vector for all connections by maximizing an overall system utility, can achieve high system throughput and keep the performance measures of all connections to meet their QoS requirements. Simulation results show that the CNNU-based scheduler attains the average system throughput greater than the EXP and the HOLPRO scheduling schemes by an amount of 23% and 33%, respectively, in the QoS guaranteed region.

A utility-based scheduling algorithm with differentiated QoS provisioning for multimedia CDMA cellular networks

We propose a utility-based scheduling algorithm with three generalized design aspects of link adaptation, QoS requirement achievement, and weighted fairness for a multimedia CDMA network. Both dedicated and shared channels serve different classes of service. Per class QoS requirements are defined by both packet level, such as BER, and call level, such as delay bound, packet dropping ratio, and minimum transmission rate. The utility function of each connection is the radio resource function weighted by both the QoS requirement achievement function and weighted fairness function. The system resource is scheduled by maximizing the overall system utility while the weighted fairness and the QoS requirements are kept. The optimal scheduling solution is derived as a resource assignment vector for active connections by solving the optimization of the overall utility function via a polymatroid structure.

A cellular neural network and utility-based scheduler for multimedia CDMA cellular networks

In this paper, a cellular neural network and utility (CNNU)-based scheduler is proposed for multimedia CDMA cellular networks supporting differentiated quality-of-service (QoS). The cellular neural network is powerful for complicated optimization problems and implementable by circuits with rapid convergence to a desired equilibrium; the utility-based scheduling algorithm can efficiently utilize the radio resource for system and provide QoS requirements and fairness for connections. A relevant utility function for each connection is here defined as its radio resource function further weighted by both a QoS requirement deviation function and a fairness compensation function. The CNNU-based scheduler determines a radio resource assignment vector for all connections so that the overall system utility is maximized and the system throughput can be achieved as high as possible. At the same time, the performance measures of all connections are kept closed to their QoS requirements in an efficient way.

Radio resource index for WCDMA cellular systems

In this letter, a radio resource index (RRI) is derived to estimate the radio resources of a connection in WCDMA cellular systems. An analytical model is presented and large deviation techniques are used. The RRI can transform traffic parameters and multiple quality-of-service (QoS) requirements into a measure of radio resources using a unified metric.

The radio resource index for real-time service in WCDMA cellular systems

A radio resource index (RRI) is derived to estimate the radio resource required for call connection in WCDMA cellular systems. An analytical model is proposed and large deviation techniques are adopted to obtain the RRI. The RRI can transform traffic parameters and quality-of-service (QoS) requirements of the call connection into a resource measure in a unified metric, while keeping: QoS requirements of existing calls guaranteed.